Brune, M., Meisen, T., & Pomp, A. (2024). "Survey of Deep Learning-Based Methods for FMCW Radar Odometry and Ego-Localization" , Applied Sciences , 14 (6), 2267.

Bohn, C., Freeman, I., Tercan, H., & Meisen, T. (2024). Task Weighting through Gradient Projection for Multitask Learning.

Hahn, Y., Kienitz, P., Wönkhaus, M., Meyes, R., & Meisen, T. (2024). "Towards Accurate Flood Predictions: A Deep Learning Approach Using Wupper River Data" , Water , 16 (23),

Alves-Gomes, M., Meisen, P., & Meisen, T. (2024). Towards Lifelong Learning Embeddings: An Algorithmic Approach to Dynamically Extend Embeddings.

Hoseini, S., Burgdorf, A., Paulus, A., Meisen, T., Quix, C., & Pomp, A. (2024). "Towards LLM-augmented Creation of Semantic Models for Dataspaces" in The Second International Workshop on Semantics in Dataspaces, co-located with the Extended Semantic Web Conference .

Hadwiger, S., Kube, D., Lavrik, V., & Meisen, T. (2024). "Towards Precision in Motion: Investigating the Influences of Curriculum Learning based on a Multi-Purpose Performance Metric for Vision-Based Forklift Navigation" in 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE) , IEEE 796—803.

Alves Gomes, M., & Meisen, T. (2023). "A review on customer segmentation methods for personalized customer targeting in e-commerce use cases" , Information Systems and e-Business Management .

Bulow, F., & Meisen, T. (2023). "A review on methods for state of health forecasting of lithium-ion batteries applicable in real-world operational conditions" , Journal of Energy Storage , 57 , 105978.

Braken, R., Paulus, A., Pomp, A., & Meisen, T. (2023). "An Evaluation of Link Prediction Approaches in Few-Shot Scenarios" , Electronics , 12 (10), 2296.

Paulus, A., Burgdorf, A., Pomp, A., & Meisen, T. (2023). "Collaborative Filtering Recommender System for Semantic Model Refinement" in 2023 IEEE 17th International Conference on Semantic Computing (ICSC) , IEEE 183—190.

Waubert-de-Puiseau, C., Tercan, H., & Meisen, T. (2023). "Curriculum Learning in Job Shop Scheduling using Reinforcement Learning" .

Samsonov, V., Chrismarie, E., Köpken, H., Bär, S., Lütticke, D., & Meisen, T. (2023). "Deep representation learning and reinforcement learning for workpiece setup optimization in CNC milling" , Production Engineering .

Maiero, J., Fehling, C. D., & Müser, S. (2023). "Does Higher Education Need Virtual Reality? A Survey" in 2023 11th International Conference on Information and Education Technology (ICIET) , IEEE 6—13.

Müser, S., Maiero, J., Fehling, C. D., Gilbert, D., Eroglu, S., Bachmann, D., Wiederspohn, S., & Meyer, J. (2023). "Konzeption und Evaluation einer virtuellen Lernumgebung für die Hochschullehre" , MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung , 51 , 345—372.

Puiseau, C., Zey, L., Demir, M., Tercan, H., & Meisen, T. (2023). "On The Effectiveness Of Bottleneck Information For Solving Job Shop Scheduling Problems Using Deep Reinforcement Learning" , Proceedings of the Conference on Production Systems and Logistics: CPSL 2023-2 .